Multi-model adaptive switching control of a nonlinear system and its applications in a smelting process of fused magnesia. (July 2022) - Fu, Yue; Li, Bao; Fu, Jun
Abstract: In this paper, for a class of discrete-time nonlinear affine systems with jump parameters, a multi-model adaptive switching control method is proposed. Firstly, by introducing an intermediate virtual variable, the complex nonlinear system is converted into a linear-like system and the nonlinear switching control problem is simplified with a linear-like switching control problem. Then for the linear-like systems with jump parameters, a multi-model adaptive switching controller based on higher-order disturbance observers is derived. The controller is composed of M − 2 controllers with fixed parameters, an adaptive controller that can be reinitialized and an adaptive controller that can run freely. For the adaptive controllers, the extended recursive least square algorithm is adopted, which effectively weakens the interaction between the model identification error and the observation error of disturbance. Stability and convergence of the closed-loop system are also analyzed by resorting to the key technique lemma. Finally, simulation experiments for a smelting process of fused magnesia are conducted and the results illustrate the effectiveness and superiority of the proposed control method. Highlights: The nonlinear control problem is simplified to a linear one through the virtural transformation. The extended RLS algorithm is adapted to weaken the error interactions. The Stability and convergence of the closed-loop system is analyzed. The Simulations are conducted in a smelting process of fused magnesia.